Python Forum

First post, so I apologize for any improper post etiquette, and am receptive to feedback. I have a data frame containing NBA games from the past several seasons(6000+ rows) and need to update some values to adjust for teams who have built new arenas. Data set looks like this

Output:
 Date             Visitor  V_PTS                 Home  H_PTS  \
0 2012-10-30 19:00:00  Washington Wizards     84  Cleveland Cavaliers     94   
1 2012-11-02 19:30:00       Chicago Bulls    115  Cleveland Cavaliers     86   
2 2012-11-17 19:30:00    Dallas Mavericks    103  Cleveland Cavaliers     95   

   Attendance                Arena         Location  Capacity Yr Arena Opened  \
0       20562  Quicken Loans Arena  Cleveland, Ohio     20562            1994   
1       20562  Quicken Loans Arena  Cleveland, Ohio     20562            1994   
2       18633  Quicken Loans Arena  Cleveland, Ohio     20562            1994   

    Season  
0  2012-13  
1  2012-13  
2  2012-13  

Here is what I have so far for a function I am trying to apply with no success. Any help would be appreciated on what I am doing wrong or if there is a better way to do this and also how to apply the function properly to the df which I named NBA.

def old_arena(home):
    for team in home :
        if (team == ('Detroit Pistons') & (nba['Date']<'2016-9-30')):
            nba['Arena'] = 'The Palace of Auburn Hills'
            nba['Location'] = 'Auburn Hills, Michigan'
            nba['Capacity'] = 22076
            nba['Yr Arena Opened'] = 1988
        elif ((team == 'Sacremento Kings') & (nba['Date']<'2017-9-5')):
            nba['Arena'] = 'Sleep Train Arena'
            nba['Capacity'] = 17317
            nba['Yr Arena Opened'] = 1988

You are abusing pandas - here's an example of selecting rows by condition - assuming that your column Date is of

dtype=datetime64

games[(games['Date'] < pd.Timestamp('2016-9-30')) & (games['Visitor'] == 'Chicago Bulls')]

You cannot change cells in a row like that - but that (at the moment) is beyond my knowledge

PS Googled

Quote:update selected dataframe row

, got this answer, elementary Watson